Keyword Extraction

19 papers with code • 4 benchmarks • 4 datasets

Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document (Source: Wikipedia).

Most implemented papers

sCAKE: Semantic Connectivity Aware Keyword Extraction

SDuari/sCAKE-and-LAKE 27 Nov 2018

Combination of the proposed graph construction and scoring methods leads to a novel, parameterless keyword extraction method (sCAKE) based on semantic connectivity of words in the document.

Combining Graph Degeneracy and Submodularity for Unsupervised Extractive Summarization

Tixierae/EMNLP2017_NewSum WS 2017

We present a fully unsupervised, extractive text summarization system that leverages a submodularity framework introduced by past research.

YAKE! Keyword extraction from single documents using multiple local features

LIAAD/yake ECIR 2018 2018

In this paper, we present YAKE!, a novel feature-based system for multi-lingual keyword extraction from single documents, which supports texts of different sizes, domains or languages.

Efficient Generation and Processing of Word Co-occurrence Networks Using corpus2graph

zzcoolj/corpus2graph WS 2018

Corpus2graph is an open-source NLP-application-oriented tool that generates a word co-occurrence network from a large corpus.

RaKUn: Rank-based Keyword extraction via Unsupervised learning and Meta vertex aggregation

SkBlaz/rakun 15 Jul 2019

Keyword extraction is used for summarizing the content of a document and supports efficient document retrieval, and is as such an indispensable part of modern text-based systems.

Complex Network based Supervised Keyword Extractor

SDuari/Supervised-Keyword-Extraction 26 Sep 2019

This shows that the proposed method is independent of the domain, collection, and language of the training corpora.

Semantic Sensitive TF-IDF to Determine Word Relevance in Documents

vfcarida/Semantic-Sensitive-TF-IDF-to-Determine-Word-Relevance-in-Documents 6 Jan 2020

Keyword extraction has received an increasing attention as an important research topic which can lead to have advancements in diverse applications such as document context categorization, text indexing and document classification.

TNT-KID: Transformer-based Neural Tagger for Keyword Identification

matej.martinc/tnt_kid 20 Mar 2020

With growing amounts of available textual data, development of algorithms capable of automatic analysis, categorization and summarization of these data has become a necessity.

Keywords lie far from the mean of all words in local vector space

epapagia/LocalVectors_AKE 21 Aug 2020

Keyword extraction is an important document process that aims at finding a small set of terms that concisely describe a document's topics.